Karen Yin-Yee Ng created SPARK-10578:
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Summary: pyspark.ml.classification.RandomForestClassifer does not
return `rawPrediction` column
Key: SPARK-10578
URL: https://issues.apache.org/jira/browse/SPARK-10578
Project: Spark
Issue Type: Bug
Components: ML
Affects Versions: 1.4.1, 1.4.0
Environment: CentOS, PySpark 1.4.1, Scala 2.10
Reporter: Karen Yin-Yee Ng
To use `pyspark.ml.classification.RandomForestClassifer` with
`BinaryClassificationEvaluator`, a column called `rawPrediction` needs to be
returned by the `RandomForestClassifer`.
The PySpark documentation example of `logisticsRegression`outputs the
`rawPrediction` column but not `RandomForestClassifier`.
Therefore, one is unable to use `RandomForestClassifier` with the evaluator nor
put it in a pipeline with cross validation.
A relevant piece of code showing how to reproduce the bug can be found at:
https://gist.github.com/karenyyng/cf61ae655b032f754bfb
A relevant post due to this possible bug can also be found at:
http://apache-spark-user-list.1001560.n3.nabble.com/Issue-with-running-CrossValidator-with-RandomForestClassifier-on-dataset-td23791.html
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